Corpus ID: 219963093

Differentially-Private Federated Linear Bandits

  title={Differentially-Private Federated Linear Bandits},
  author={Abhimanyu Dubey and Alex 'Sandy' Pentland},
The rapid proliferation of decentralized learning systems mandates the need for differentially-private cooperative learning. In this paper, we study this in context of the contextual linear bandit: we consider a collection of agents cooperating to solve a common contextual bandit, while ensuring that their communication remains private. For this problem, we devise \textsc{FedUCB}, a multiagent private algorithm for both centralized and decentralized (peer-to-peer) federated learning. We provide… Expand

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